- What is AI agent governance?
- AI agent governance is the set of controls that determine what an autonomous agent may access, spend, execute and approve — and the evidence that proves what it actually did. In practice it combines written mandates, deterministic policy evaluation, named human approvers, an audit trail and immediate revocation.
- Why is a prompt or system message not a control?
- A prompt expresses intent; it does not enforce a limit. A model can be persuaded, can misread context, and cannot produce an auditable record of its own constraints. Enforcement has to sit outside the model, in code that evaluates each action against explicit rules.
- How much autonomy should an agent have?
- Start with observation, move to human approval, then to bounded autonomy inside written limits, and widen those limits only on demonstrated behaviour. Each stage should be a deliberate decision with an owner, not a default.
- What does a finance or compliance team need to see?
- Which agents hold authority, how much of it has been drawn, which actions were refused and why, who approved the exceptions, and how quickly authority can be withdrawn. If those five answers require an engineer, the governance model is incomplete.